Constrained networks include, for example, Low power and Lossy Networks (LLNs), such as sensor networks. These constrained networks have a myriad of applications, such as Smart Grid, Smart Cities, home and building automation, etc. Various challenges are presented with LLNs, such as lossy links, low bandwidth, battery operation, low memory and/or processing capability, etc. Large-scale internet protocol (IP) smart object networks pose a number of technical challenges. For instance, the degree of density of such networks (such as Smart Grid networks with a large number of sensors and actuators, smart cities, or advanced metering infrastructure (AMI) networks) may be extremely high. For example, it is not rare for each node to see several hundreds of neighbors. This architecture is particularly problematic for LLNs, where constrained links can wreak havoc on data transmission.
Network developers would like to have the endpoints of the network know the electrical phase to which the devices are connected. One important benefit of knowing the phase information is that this knowledge allows utility companies and other system managers to make better decisions about load balancing on the distribution network. While physical field inspection may provide the system manager with some information about the phase to which each endpoint is connected, the information is often inaccurate or insufficient. Current technologies do not provide the ability to determine the phase of each of the network devices.